Age-Stratified Analysis of COVID-19 Outcome Using Machine Learning Predictive Models

Since the emergence of COVID-19, most health systems around the world have experienced a series of spikes in the number of infected patients, leading to collapse of the health systems in many countries. The use of clinical laboratory tests can serve as a discriminatory method for disease severity, defining the profile of patients with a higher risk of mortality. In this paper, we study the results of applying predictive models to data regarding COVID-19 outcome, using three datasets after age stratification of patients. The extreme gradient boosting (XGBoost) algorithm was employed as the predictive method, yielding excellent results. The area under the receiving operator characteristic curve (AUROC) value was 0.97 for the subgroup of patients up to 65 years of age. In addition, SHAP (Shapley additive explanations) was used to analyze the feature importance in the resulting model

La red MARHIS. Una alianza estratégica para la ingeniería y las EERR marinas en España

MARHIS agradece la financiación recibida por MINECO a través de las Acciones de dinamización “Redes de Excelencia” Convocatoria 2015

Fast Ground Filtering of Airborne LiDAR Data Based on Iterative Scan-Line Spline Interpolation

Over the last two decades, a wide range of applications have been developed from Light Detection and Ranging (LiDAR) point clouds. Most LiDAR-derived products require the distinction between ground and non-ground points. Because of this, ground filtering its being one of the most studied topics in the literature and robust methods are nowadays available. However, these methods have been designed to work with offline data and they are generally not well suited for real-time scenarios. Aiming to address this issue, this paper proposes an efficient method for ground filtering of airborne LiDAR data based on scan-line processing. In our proposal, an iterative 1-D spline interpolation is performed in each scan line sequentially. The final spline knots of a scan line are taken into account for the next scan line, so that valuable 2-D information is also considered without compromising computational efficiency. Points are labelled into ground and non-ground by analysing their residuals to the final spline. When tested against synthetic ground truth, the method yields a mean kappa value of 88.59% and a mean total error of 0.50%. Experiments with real data also show satisfactory results under visual inspection. Performance tests on a workstation show that the method can process up to 1 million points per second. The original implementation was ported into a low-cost development board to demonstrate its feasibility to run in embedded systems, where throughput was improved by using programmable logic hardware acceleration. Analysis shows that real-time filtering is possible in a high-end board prototype, as it can process the amount of points per second that current lightweight scanners acquire with low-energy consumptionThis work was supported by the Ministry of Education, Culture, and Sport, Government of Spain (Grant Number TIN2016-76373-P), the Consellería de Cultura, Educación e Ordenación Universitaria (accreditation 2016–2019, ED431G/08, and ED431C 2018/2019), and the European Union (European Regional Development Fund—ERDF)S

Synthesis and characterization of new tail-to-tail dimers of bile acids with different spacers

The 13th International Electronic Conference on Synthetic Organic Chemistry session Polymer and Supramolecular ChemistryNew dimeric steroid-based surfactants derived from 3α,7α,12α-trihydroxy-5β- cholan-24-amine (steroid residue) and isophthalic acid, 5,5'-biisobenzofuran-1,1',3,3'- carboxylic acid and succinic acid (spacers) were synthesized and structurally characterized by NMR techniques. The first spacer was also employed to synthesize the dimer corresponding to the 3α,12α-dihydroxy-5β-cholan-24-amine residue. In all cases the steroid residues are tail-to-tail linked through amide bonds with the spacersAuthors thank the Ministerio de Ciencia y Tecnología (Project MAT2004-04606) and the Xunta de Galicia (PGIDIT05PXIC26201PN) for financial suppor

Theoretical calculations on conformations of bile-acid based dimers. Interactions with ibuprofen

The 13th International Electronic Conference on Synthetic Organic Chemistry session Polymer and Supramolecular ChemistryAn AM1 semiempirical method (Gaussian 03) was used to perform molecular structure optimizations in gas phase of two tail-to-tail bile acid-based dimers by an isophthalic acid bridge. The method was also used to study the interactions with the potential guest ibuprofen with the idea of applicative resultsAuthors thank the Ministerio de Ciencia y Tecnología (Project MAT2004-04606) and the Xunta de Galicia (PGIDIT05PXIC26201PN) for financial suppor

Synthesis and Characterization of a New Gemini Surfactant Derived from 3a,7a,12a-trihydroxy-5ß-cholan-24-amine (Steroid Residue) and Ethylenediamintetraacetic Acid (Spacer)

The 12th International Electronic Conference on Synthetic Organic Chemistry session Supramolecular ChemistryA new gemini steroid surfactant derived from 3a,7a,12a-trihydroxy-5ß-cholan-24-amine (steroid residue) and ethylenediamintetraacetic acid (spacer) was synthesized and characterized in aqueous solution by surface tension measurements and fluorescence intensity of pyrene. These techniques evidence the existence of a threshold concentration, cac, below which a three layers film is formed at the air-water interface. At high concentrations, the intensity ratio of the vibronic peaks of pyrene, I1/I3, (= 0.81) is very close to published values for sodium cholate micelles, indicating that the probe is located in a region with a very low polarity and far from waterThe authors from USC thank the Ministerio de Ciencia y Tecnología (Project MAT2004-04606) and Xunta de Galicia (PGIDIT05PXIC26201PN) for financial suppor

Machine Learning Applied to Clinical Laboratory Data in Spain for COVID-19 Outcome Prediction: Model Development and Validation

Artículo publicado en la revista "JOURNAL OF MEDICAL INTERNET RESEARCH", indexada en JCR (2019) en el Q1 de "HEALTH CARE SCIENCES & SERVICES" (5/102) y "MEDICAL INFORMATICS" (2/27); Impact Factor 5.03.Background: The COVID-19 pandemic is probably the greatest health catastrophe of the modern era. Spain’s health care system has been exposed to uncontrollable numbers of patients over a short period, causing the system to collapse. Given that diagnosis is not immediate, and there is no effective treatment for COVID-19, other tools have had to be developed to identify patients at the risk of severe disease complications and thus optimize material and human resources in health care. There are no tools to identify patients who have a worse prognosis than others. Objective: This study aimed to process a sample of electronic health records of patients with COVID-19 in order to develop a machine learning model to predict the severity of infection and mortality from among clinical laboratory parameters. Early patient classification can help optimize material and human resources, and analysis of the most important features of the model could provide more detailed insights into the disease. Methods: After an initial performance evaluation based on a comparison with several other well-known methods, the extreme gradient boosting algorithm was selected as the predictive method for this study. In addition, Shapley Additive Explanations was used to analyze the importance of the features of the resulting model. Results: After data preprocessing, 1823 confirmed patients with COVID-19 and 32 predictor features were selected. On bootstrap validation, the extreme gradient boosting classifier yielded a value of 0.97 (95% CI 0.96-0.98) for the area under the receiver operator characteristic curve, 0.86 (95% CI 0.80-0.91) for the area under the precision-recall curve, 0.94 (95% CI 0.92-0.95) for accuracy, 0.77 (95% CI 0.72-0.83) for the F-score, 0.93 (95% CI 0.89-0.98) for sensitivity, and 0.91 (95% CI 0.86-0.96) for specificity. The 4 most relevant features for model prediction were lactate dehydrogenase activity, C-reactive protein levels, neutrophil counts, and urea levels. Conclusions: Our predictive model yielded excellent results in the differentiating among patients who died of COVID-19, primarily from among laboratory parameter values. Analysis of the resulting model identified a set of features with the most significant impact on the prediction, thus relating them to a higher risk of mortality

Complexation of 3α,7α,12α-trihydroxy-5β-cholan-24-amine by β- and γ-cyclodextrins

The 13th International Electronic Conference on Synthetic Organic Chemistry session Polymer and Supramolecular ChemistryThe binding constants, standard molar enthalpy, Gibbs free energy, and entropy changes were determined for the formation of inclusion complexes between 3α,7α,12α- trihydroxy-5β-cholan-24-amine, C24NH2, and β-cyclodextrin and γ-cyclodextrin. The stoichiometry of both complexes is 1:1 in agreement with previously reported results for other trihydroxy bile salts. The equilibrium constant values for the formation of the inclusion complex are similar as well. The structure of the C24NH2/γ-cyclodextrin complex was studied by ROESY experiments. These results suggest that B, C and Drings of the steroid skeleton, as well as the side chain, interact with the cyclodextrin cavity, while the A ring of the steroid nucleus remains outside the cavityThe authors from USC thank the Ministerio de Ciencia y Tecnología (Project MAT2004-04606) and Xunta de Galicia (PGIDIT05PXIC26201PN) for financial suppor

Complexation of adamantyl derivatives by a β–cyclodextrin dimer.

The 13th International Electronic Conference on Synthetic Organic Chemistry session Polymer and Supramolecular ChemistryThe binding constants, standard molar enthalpy, Gibbs free energy, and entropy changes were determined for the formation of complexes between adamantyl derivatives and a β-cyclodextrin dimer. It is concluded that, within experimental error, the two cyclodextrin residues in the dimer behave independent to each other when complexing the adamantyl derivativesThe authors from USC thank the Ministerio de Ciencia y Tecnología (Project MAT2004-04606) and Xunta de Galicia (PGIDIT05PXIC26201PN) for financial suppor

Supramolecular polymer formed by ditopic cyclodextrin and ditopic adamantane derivatives

The 12th International Electronic Conference on Synthetic Organic Chemistry session Supramolecular ChemistryNovel host-guest supramolecular copolymers have been prepared from a ß-cyclodextrin (binded to ethylenediamintetraacetic acid, EDTA) dimer and a ditopic guest with two adamantyl groups bound to pyromellitic acid. Molecular weight and molecular size were determined from static and dynamic light scattering measurements (SLS and DLS, respectively). The analysis of results suggests that the supramolecular polymer adopts a shruck structure with an average molecular weight value of Mn =(1.51±0.02)×104 g·mol-1 (degree of polymerization equal to 5)The authors from USC thank the Ministerio de Ciencia y Tecnología (Project MAT2004-04606) and Xunta de Galicia (PGIDIT05PXIC26201PN) for financial suppor